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1.4 KiB
1.4 KiB
Reduction with CK Tile
This example demonstrates parallel reduction (sum, max, etc.) using the CK Tile programming model, a core operation for normalization, statistics, and aggregation in deep learning.
Algorithm and Math
Given a tensor X and a reduction axis, compute:
-
Sum:
Y = \sum_i X_i -
Max:
Y = \max_i X_i -
Mean:
Y = \frac{1}{N} \sum_i X_i -
Tilewise Reduction: Each thread block reduces a tile (block) of the input, using shared memory and register accumulation for efficiency.
Tile Programming Model
- Tiles: Each thread block processes a tile (block) of the input tensor.
- Pipeline: Modular, can be extended for fused reductions or post-processing.
Build & Run
mkdir build && cd build
sh ../script/cmake-ck-dev.sh ../ <arch>
make tile_example_reduce -j
./bin/tile_example_reduce -?
Source Structure
- Kernel:
reduce.hpp(tile-programming kernel template) - Executable:
reduce.cpp(argument parsing, kernel launch) - Build:
CMakeLists.txt
Related CK Tile Examples
- 03_gemm: GEMM with tiles
- 04_img2col: im2col transformation
- 06_permute: Permutation with tiles
For distribution, see include/ck_tile/tile_program/tile_distribution/.